R version 4.0.3 (2020-10-10) – “Bunny-Wunnies Freak Out”
Packages used for NMDS: vegan (version 2.5-7)
The document shows a series of NMDS ordinations for reference Coastal benthic communities in Virginia with environmental characteristics overlaid to evaluate natural differences in community compositions across coastal regions in Virginia. These NMDS will support the Genus level IBI development process. No West Virginia DEP data is used in this analysis.Reference sites were evaluated by regional biologists.
The dataset used includes all coastal reference stations collected in Virginia that were deemed reference through a series or water quality parameter filters and regional biologist review. Coastal stations were considered to be located in the Southeastern Plains and MidAtlantic Coastal Plains ecoregion. Communities were deemed to have different biological communities based on ordinations conducted on the entire reference dataset as is demonstrated in the document titled “NMDS for Reference Streams”. If stations appeared in the dataset more than 4 times, then the most recent 4 samples were used and the rest removed. Samples that had a total number of taxa below 100 collected at the time of sampling were also removed. Taxa that occurred in the dataset <= 5% of the time were removed. The data was log10 +1 transformed. Environmental factors were compiled for each station and used to plot over the NMDS to show environmental variation associated with the community matrix. The envfit function in Vegan was used to plot the continuous environmental variables. Some environmental variables like precipitation, slope, and elevation have not been calculated for all watersheds yet and will be added at a later date.
The first step was to read in the reference site bug taxa list and environmental factors dataset for each station. Join the environmental dataset with the bug dataset to account for multiple observations of each station and collection date and time.
Check to make sure the bug and environmental join was successful:
Number of rows in Community Matrix: 854
Number or rows in Environmental Matrix: 164
The data was log10+1 transformed. Rare taxa (<=5%) were removed.
## Run 0 stress 0.1913284
## Run 1 stress 0.1924667
## Run 2 stress 0.1915459
## ... Procrustes: rmse 0.006251724 max resid 0.07083938
## Run 3 stress 0.1916266
## ... Procrustes: rmse 0.008844229 max resid 0.07277868
## Run 4 stress 0.1919023
## Run 5 stress 0.1913193
## ... New best solution
## ... Procrustes: rmse 0.003307878 max resid 0.03593767
## Run 6 stress 0.1913334
## ... Procrustes: rmse 0.001913764 max resid 0.01691334
## Run 7 stress 0.1913941
## ... Procrustes: rmse 0.005597194 max resid 0.0467852
## Run 8 stress 0.1913243
## ... Procrustes: rmse 0.005018307 max resid 0.05009633
## Run 9 stress 0.1915474
## ... Procrustes: rmse 0.008015682 max resid 0.07167867
## Run 10 stress 0.1935596
## Run 11 stress 0.1920066
## Run 12 stress 0.1926443
## Run 13 stress 0.1914415
## ... Procrustes: rmse 0.006649738 max resid 0.0515911
## Run 14 stress 0.1916249
## ... Procrustes: rmse 0.009250845 max resid 0.07365771
## Run 15 stress 0.1920078
## Run 16 stress 0.1915115
## ... Procrustes: rmse 0.005802026 max resid 0.06579275
## Run 17 stress 0.1915456
## ... Procrustes: rmse 0.007689424 max resid 0.07096864
## Run 18 stress 0.1914807
## ... Procrustes: rmse 0.007603135 max resid 0.05318731
## Run 19 stress 0.1913217
## ... Procrustes: rmse 0.001089841 max resid 0.007633913
## ... Similar to previous best
## Run 20 stress 0.1926767
## *** Solution reached
##
## Call:
## metaMDS(comm = coastalFive[, 6:104], k = 3, trymax = 1000)
##
## global Multidimensional Scaling using monoMDS
##
## Data: coastalFive[, 6:104]
## Distance: bray
##
## Dimensions: 3
## Stress: 0.1913193
## Stress type 1, weak ties
## Two convergent solutions found after 20 tries
## Scaling: centring, PC rotation, halfchange scaling
## Species: expanded scores based on 'coastalFive[, 6:104]'
## NMDS1 NMDS2 r2 Pr(>r)
## Year 0.95310 -0.30265 0.0082 0.92
## JulianDate -0.10634 -0.99433 0.1896 0.06 .
## Latitude 0.74843 0.66321 0.3467 0.02 *
## Longitude -0.41155 0.91139 0.0935 0.24
## totalArea_sqMile 0.70300 -0.71119 0.2373 0.06 .
## ELEVMEAN 0.65464 -0.75594 0.2846 0.03 *
## SLPMEAN 0.99932 0.03675 0.4365 0.01 **
## wshdRain_mmyr 0.70928 -0.70493 0.2358 0.06 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Permutation: free
## Number of permutations: 99
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:104], grouping = samplescoresenv_coast$Season, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Fall Outside Sample Window Spring
## delta 0.6387 0.6458 0.6462
## n 68 5 89
##
## Chance corrected within-group agreement A: 0.01854
## Based on observed delta 0.643 and expected delta 0.6552
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:104], grouping = samplescoresenv_coast$US_L3NAME, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Middle Atlantic Coastal Plain Southeastern Plains
## delta 0.6147 0.6441
## n 25 137
##
## Chance corrected within-group agreement A: 0.02378
## Based on observed delta 0.6396 and expected delta 0.6552
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:104], grouping = samplescoresenv_coast$Basin_Code, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Appomattox Chowan-Dismal James-Lower Potomac-Lower Rappahannock
## delta 0.5032 0.6767 0.631 0.5901 0.5682
## n 3 29 36 6 22
## Small Coastal York
## delta 0.5896 0.6369
## n 21 45
##
## Chance corrected within-group agreement A: 0.04903
## Based on observed delta 0.623 and expected delta 0.6552
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:104], grouping = samplescoresenv_coast$ASSESS_REG, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## NRO PRO TRO
## delta 0.6483 0.6269 0.6086
## n 37 104 21
##
## Chance corrected within-group agreement A: 0.03934
## Based on observed delta 0.6294 and expected delta 0.6552
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##Bioregion: Coastal
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:104], grouping = samplescoresenv_coast$Bioregion, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Coast
## delta 0.6552
## n 162
##
## Chance corrected within-group agreement A: 0
## Based on observed delta 0.6552 and expected delta 0.6552
##
## Significance of delta: 1
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:104], grouping = samplescoresenv_coast$Gradient, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## MACS Riffle
## delta 0.6535 0.5209
## n 154 8
##
## Chance corrected within-group agreement A: 0.01261
## Based on observed delta 0.6469 and expected delta 0.6552
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:104], grouping = samplescoresenv_coast$Order, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## 1 2 3 4 5 6
## delta 0.6136 0.602 0.6157 0.6783 0.6069 0.3877
## n 33 43 35 35 14 2
##
## Chance corrected within-group agreement A: 0.05128
## Based on observed delta 0.6216 and expected delta 0.6552
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:104], grouping = samplescoresenv_coast$StreamCate, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## Large Medium Small
## delta 0.6727 0.6157 0.6327
## n 51 35 76
##
## Chance corrected within-group agreement A: 0.02065
## Based on observed delta 0.6416 and expected delta 0.6552
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:104], grouping = samplescoresenv_coast$WQS_CLASS, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## III VII
## delta 0.6538 0.6504
## n 120 42
##
## Chance corrected within-group agreement A: 0.003482
## Based on observed delta 0.6529 and expected delta 0.6552
##
## Significance of delta: 0.011
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:104], grouping = samplescoresenv_coast$BioregionSeason, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## LargeCoastFall LargeCoastOutside Sample Window LargeCoastSpring
## delta 0.6833 0.4415 0.6256
## n 20 2 29
## MediumCoastFall MediumCoastOutside Sample Window MediumCoastSpring
## delta 0.6092 0.5285 0.5906
## n 14 2 19
## SmallCoastFall SmallCoastOutside Sample Window SmallCoastSpring
## delta 0.6131 NaN 0.6335
## n 34 1 41
##
## Chance corrected within-group agreement A: 0.04894
## Based on observed delta 0.6231 and expected delta 0.6552
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999
##
## Call:
## mrpp(dat = bugsnms_coast[, 6:104], grouping = samplescoresenv_coast$Bioregionsize, distance = "bray")
##
## Dissimilarity index: bray
## Weights for groups: n
##
## Class means and counts:
##
## LargeCoast MediumCoast SmallCoast
## delta 0.6727 0.6157 0.6327
## n 51 35 76
##
## Chance corrected within-group agreement A: 0.02065
## Based on observed delta 0.6416 and expected delta 0.6552
##
## Significance of delta: 0.001
## Permutation: free
## Number of permutations: 999